India’s AI revolution isn’t just about code, it’s about voices. For local large language models (LLMs) to work well, they need massive amounts of regional voice data.

Unlike text, voice captures accents, tones, and literacy gaps, making AI more inclusive. But there’s a big problem: quality datasets in Indian languages are scarce. That’s why start-ups, researchers, and even big tech are rushing to collect them.

Take Rian.io, where voice-over artists record stories, reports, and ads in Hindi, Marathi, and English. Or AiVanta, which pays artists (sometimes lakhs a month) every time their recorded voices are reused in AI-generated videos. Meanwhile, Quansys AI built its dataset by asking friends to record paragraphs in their native tongues via WhatsApp. Even non-profits like IISc’s Project Vaani are gathering 150,000 hours of speech from across India.

The prize is huge: India’s voice commerce market is expected to grow from $1.57 billion in 2024 to $7.47 billion by 2030. Whoever builds the richest, most accurate voice datasets could shape the future of AI assistants, chatbots, and commerce in India.

In short: the real AI race isn’t in Silicon Valley, it’s in India’s dialects.